Secondary Logo

Journal Logo

Epidemiology and Prevention

Increase in CD4 Count Among New Enrollees in HIV Care in the Modern Antiretroviral Therapy Era

Haines, Charles F. MD, PhD*; Fleishman, John A. PhD; Yehia, Baligh R. MD, MPP, MSHP; Berry, Stephen A. MD, PhD*; Moore, Richard D. MD, MHS*; Bamford, Laura P. MD, MSCE‡,§; Gebo, Kelly A. MD, MPH*for the HIV Research Network

Author Information
JAIDS Journal of Acquired Immune Deficiency Syndromes: September 1st, 2014 - Volume 67 - Issue 1 - p 84-90
doi: 10.1097/QAI.0000000000000228
  • Free

Abstract

BACKGROUND

In September 2006, the Centers for Disease Control and Prevention (CDC) recommended HIV testing in all health-care settings.1 The revision was catalyzed in part by evidence that decreasing the time to presentation leads to improved outcomes2,3 and decreased secondary transmission,4 and by studies demonstrating the cost effectiveness of increased screening.5–7 Increased screening detects asymptomatic HIV infections earlier, shortening the time from HIV infection to presentation to care.

However, before the benefits of increased screening can be realized, individuals must be linked to HIV care and treatment. Only about 80% of persons living with HIV in the United States know their HIV status, of whom only 75%–77% have ever presented for care.8,9 Improvements in both screening and linkage to care at the population level would decrease the average time from HIV infection to presentation to HIV care and drive up the CD4 count (CD4) at presentation to HIV care.

Results of prior studies of CD4 at presentation to care in the modern antiretroviral therapy era have been mixed. Althoff et al10 demonstrated a significant increase in median CD4 at presentation from 256 to 317 cells per cubic millimeter between 1997 and 2007 in the North American-AIDS Cohort Collaboration on Research and Design. In contrast, HIV Outpatient Study investigators showed no increase in CD4 at diagnosis between 2000 and 2009.11 Additionally, these studies demonstrate disparities in late presentation by race/ethnicity, HIV risk factor, and age. Given the conflicting results of these prior reports, we examined the CD4 at enrollment to care among patients enrolled in a multicenter HIV cohort from 2003 to 2011 to determine if CD4 at enrollment changed over time, in particular, following the CDC guideline revision. We also sought to examine possible racial/ethnic, HIV risk, and age disparities in enrollment CD4 trends.

METHODS

Participants

The HIV Research Network (HIVRN) is a consortium of primary and subspecialty medical care providers at 18 clinical sites for HIV-infected adult and pediatric patients.12 The analyses included 17 sites that collect comprehensive inpatient and outpatient use data. One pediatric site had no subjects eligible for the study (all <18 years old) and was excluded. One adult site was excluded from the 2011 data, because enrollment during this year was reported as the date of a medical practice merger rather than the actual date of enrollment to HIV care. Data from this site for 2003–2010 were retained. Sites are located in the Eastern (7), Midwestern (1), Southern (5), and Western United States (4). Fourteen sites have academic affiliations; 4 are community based. Analyses were limited to adult patients (≥18 years old) who enrolled at an HIVRN site between January 1, 2003, and December 31, 2011.

Data Collection

Participating sites abstract clinical and demographic data elements from patients' medical records; abstracted data are assembled into a uniform database.13–16 Abstracted data were sent in electronic format to a data-coordinating center. After quality control and verification, these data were combined across sites to construct a multisite database. The study was approved by the Institutional Review Board of the Johns Hopkins School of Medicine and by each of the participating sites. Institutional review boards at some clinics require written informed consent; others waived the requirement because only existing deidentified data were collected.

Definitions

New presenters were defined as newly enrolled subjects having (1) HIV RNA >400 copies per milliliter at enrollment, (2) no use of antiretroviral therapy after the enrollment CD4, and (3) no HIVRN clinic visits before enrollment month. Demographics collected were age (categorized in decades), race/ethnicity [white, black, Hispanic, and other/unknown (OTH)], gender, and HIV risk factors, coded as men who have sex with men (MSM), heterosexual transmission, injection drug use (IDU), and OTH. In subjects with multiple behavioral HIV risk factors, a single category was designated based on the following order of priority: IDU, MSM, heterosexual transmission, OTH. CD4 and HIV-1 RNA at enrollment were defined as the measurement nearest to enrollment but not >6 months before or after enrollment. Subjects without a CD4 and viral load within 6 months of enrollment were excluded (n = 334).

Statistical Analyses

CD4 at enrollment was the primary outcome. Multivariable linear regression (MLR) models included age, gender, race/ethnicity, and HIV risk factor. The primary independent variable of interest was calendar year of enrollment. Enrollment year was analyzed as a continuous variable, generating a slope in the linear regression model, reflecting the change in mean CD4 per year. Based on our interest in the change in CD4 per year after the CDC guideline revision in late 2006, a knot in the linear spline was placed at 2008 (allowing 15 months for uptake of guidelines); thus, the magnitude of the (linear) association between year and CD4 (ie, the slope) could change between 2003–2007 and 2008–2011. All MLR analyses were adjusted for clinic site and used robust standard errors to account for clustering. Interactions between spline terms and each demographic characteristic (race/ethnicity, HIV risk, and age) were tested to determine if demographic characteristics modified the effect of calendar year on CD4 count at presentation.

In separate analyses, we made comparisons within age, race/ethnicity, and HIV risk groups in a given enrollment year using an MLR including interactions between enrollment year as a categorical variable and the demographic variable of interest (age, race/ethnicity, and HIV risk), adjusting for the remaining variables. Linear combinations of coefficients were used to make comparisons among nonreferent categories.

In addition to analyzing mean CD4, we also examined change in the proportion of subjects presenting early (CD4 at enrollment ≥350 cells per cubic millimeter). We used an MLR of subjects with CD4 at enrollment ≥350 per cubic millimeter (a dichotomous variable) on year as a continuous variable with a knot in the linear spline at 2008 adjusted for demographics, HIV risk, race/ethnicity, and clinic site. This models the change in proportion of subjects presenting early from 2003–2007 to 2008–2011.

RESULTS

We identified 13,543 newly presenting patients who enrolled in the HIVRN between 2003 and 2011: 7200 between 2003 and 2007 and 6343 between 2008 and 2011. The median number of new patients was 1370 per year over the interval 2003–2007 and 1582 per year over the interval 2008–2011 (P = 0.142). The median number of new patients per year for whites was 401.5 during 2003–2007 and 382 during 2008–2011 (P = 0.54), for blacks it was 641.5 during 2003–2007 and 791 during 2008–2011 (P = 0.086), and for Hispanics it was 285 during 2003–2007 and 309 during 2008–2011 (P = 0.806). Patient characteristics stratified by time period appear in Table 1 (Fig. 1).

TABLE 1
TABLE 1:
Basic Demographic and Clinical Characteristics of New Presenters to the HIVRN Cohort From 2003 to 2011
FIGURE 1
FIGURE 1:
Mean and predicted mean CD4 count at enrollment among new presenters from 2003 to 2011 with the corresponding 95% CI. *Solid lines denote mean CD4 count at enrollment predicted by the MLR model (Table 3) for all new presenters. The dashed lines denote the actual mean CD4 count at enrollment for all new presenters. Enrollment CD4 was predicted for each subject using the adjusted MLR (Table 3), and the mean of the predicted enrollment CD4 was plotted for each enrollment year. As the inputs to the model (the demographic and behavioral risk composition of the underlying cohort) vary from year to year, the mean predicted CD4 may not be perfectly linear when plotted against calendar year.

Overall, the median CD4 at enrollment rose from 285 to 317 cells per cubic millimeter between 2003–2007 and 2008–2011 (P < 0.001) (results not shown). Median CD4 counts for 2003–2007 and 2008–2010 stratified by demographics are shown in Table 2.

TABLE 2
TABLE 2:
Median CD4 Count at Enrollment in the HIVRN Cohort From 2003–2007 to 2008–2011 Stratified by Demographics

The percentage of newly presenting subjects with CD4 at enrollment ≥350 cells per cubic millimeter increased from 40.8% in 2003–2007% to 44.3% in 2008–2011 (χ2 = 19.7, P < 0.001). There was no increase in the mean percentage of subjects with CD4 ≥350 cells per cubic millimeter during 2003–2007 (−0.19% [95% confidence interval (CI) −0.90% to 0.52%]), but there was an increase of 1.45% per year (0.73%, 2.16%) from 2008 to 2011 (results not shown).

The unadjusted annual mean CD4 at enrollment did not significantly increase over the interval 2003–2007 (−1.8 cells per cubic millimeter per year, 95% CI −5.7 to 2.2) but increased by 12.3 cells per cubic millimeter per year (95% CI 8.5 to 16.1) over the interval 2008–2011, for an overall mean increase in CD4 per year of 14.1 cells per cubic millimeter per year (7.1, 21.0) (results not shown). After adjusting for demographic factors and clinic site, the annual mean CD4 at enrollment did not significantly increase interval 2003–2007 but did significantly increase by 11.2 cells per cubic millimeter per year (7.4, 14.9) over the interval 2008–2011 (Table 3). The difference in the slope was 13.3 cells per cubic millimeter per year (6.4, 20.1) comparing 2003–2007 with 2008–2011. Females had a higher CD4 at enrollment than did males (Table 3). Variations by age, race/ethnicity, and HIV risk are addressed in the following section.

TABLE 3
TABLE 3:
MLR of the CD4 Count at Enrollment on Calendar Year in New Presenters to the HIVRN Cohort From 2003 to 2011*

Demographic Variations in CD4 Trends

Race/Ethnicity

In 2003, the adjusted mean CD4 at enrollment was 69.3 cells per cubic millimeter (28.5, 110.0) greater in whites than in blacks, 69.2 cells per cubic millimeter (25.6, 112.8) greater in whites than in Hispanics, and not significantly different between blacks and Hispanics. In 2011, the adjusted mean CD4 at enrollment was 49.3 cells per cubic millimeter (13.6, 83.0) greater in whites than in blacks, 59.0 cells per cubic millimeter (17.8, 100.2) greater in whites than in Hispanics, and not significantly different between blacks and Hispanics.

The difference in the slope between 2003 and 2007 and 2008 and 2011 was 19.3 cells per cubic millimeter per year (5.9, 32.8) for whites and 10.8 cells per cubic millimeter per year (0.9, 20.6) for blacks, but there was no significant increase in Hispanics (11.3 cells per cubic millimeter per year [−2.3, 24.9]) or OTH race [16.2 cells per cubic millimeter per year (−23.0, 55.4)] (Fig. 2 and Table 4).

FIGURE 2
FIGURE 2:
Mean and predicted mean CD4 count at enrollment among new presenters from 2003 to 2011 stratified by race/ethnicity (panel A) and age category (panel B). *Solid lines denote the mean CD4 count at enrollment predicted by the MLR model (Table 4) for all new presenters, stratified as indicated. The dashed lines denote the actual mean CD4 count at enrollment for all new presenters, stratified as indicated. Other race is not shown. Enrollment CD4 was predicted for each subject using the adjusted MLR (Table 4), and the mean of the predicted enrollment CD4 was plotted for each enrollment year. As the inputs to the model (the demographic and behavioral risk composition of the underlying cohort) vary from year to year, the mean predicted CD4 may not be perfectly linear when plotted against calendar year.
TABLE 4
TABLE 4:
MLR of CD4 Count at Enrollment on Calendar Year in New Presenters by Race/Ethnicity in the HIVRN Cohort From 2003 to 2011*

HIV Risk

In 2003, the adjusted mean CD4 at enrollment was 79.3 cells per cubic millimeter (45.0, 113.6) greater in MSM than in heterosexual risk, 70.8 cells per cubic millimeter (10.7, 130.9) greater in IDU than in heterosexual risk, and not significantly different between MSM and IDU. In 2011, the adjusted mean CD4 at enrollment was 45.2 cells per cubic millimeter (12.7, 77.7) greater in MSM than in heterosexual risk and not significantly different between either MSM and IDU or IDU and heterosexual risk.

MSM and heterosexual risk groups had an increase in the slope of CD4 at enrollment per year over the interval 2008–2011 (Table 4). There was no increase in the slopes of CD4 at enrollment per year among IDU and other HIV risk categories over the interval 2008–2011 (Table 4).

Age

For those aged >30 years, age categories did not differ in adjusted mean CD4 at enrollment in 2003. In 2003, subjects aged ≤30 years had an adjusted CD4 at enrollment greater than subjects in age categories 31–40 years [69.1 cells per cubic millimeter (30.4, 107.8)], 41–50 years [82.5 cells per cubic millimeter (40.7, 124.2)], and >50 years [72.5 cells per cubic millimeter (−13.8, 158.9)—not significant]. In 2011, the adjusted mean enrollment CD4 was 63.4 cells per cubic millimeter (17.5, 109.3) greater in 31–40 years than in >50 years, but not significantly different between either 31–40 and 41–50 years or 41–50 and >50 years. However, the adjusted 2011 mean enrollment CD4 in subjects ≤30 years was greater than in subjects in age categories 31–40 years [52.1 cells per cubic millimeter (16.0, 88.3)], 41–50 years [79.9 cells per cubic millimeter (41.8, 117.9)], and >50 years [115.5 cells per cubic millimeter (72.2, 158.8)].

CD4 at enrollment increased per year over the interval 2008–2011 for age categories ≤30, 31–40, 41–50 years, but not for >50 years (Fig. 2 and Table 4). Compared with age category >50 years, the CD4 at enrollment slope over the interval 2008–2011 was greater in age categories ≤30 years (13.4 cells per cubic millimeter per year [0.9–25.9]) and 31–40 years [17.8 cells per cubic millimeter per year (5.1–30.5)].

DISCUSSION

This study demonstrates an increase in CD4 at enrollment of 11.2 cells per cubic millimeter per year among new presenters at HIVRN sites over the interval 2008–2011 after adjusting for demographic factors and clinic site. In contrast, there was no change in CD4 count at enrollment during 2003–2007. Our data suggest that although time to presentation to care and degree of immunosuppression at presentation have been decreasing among persons living with HIV since 2008, the rate of decrease is very slow. Finally, as in previous studies, we demonstrate that there continue to be disparities in enrollment CD4 among those presenting to HIV care, with lower CD4 counts among Hispanics and blacks compared with among whites, heterosexual risk compared with MSM, and age >30 years compared with age ≤30 years.

The observed increase in CD4 at enrollment per year has several implications. We observed that the proportion CD4 ≥350 cells per cubic millimeter increased by 1.45% per year after 2008. This increase represents >500 patients per year linked to care with a CD4 ≥350 cells per cubic millimeter, to the extent that these data can be extrapolated to the national level (assuming 48,000 HIV diagnoses per year in the United States17 and 77% linkage to care8). Although encouraging, this likely represents <3% of late presenters in the United States, assuming 54% late presentation percentage.10,18

Our findings suggest that the time to presentation, as assessed by enrollment CD4, is declining slowly, and further interventions for HIV testing and linkage to care are needed. Diagnosis and linkage to care are necessary for HIV-infected patients to present for care.8,9 Recently, the US Preventative Services Task Force released a statement recommending screening of all patients aged between 15 and 64 years or patients of any age with HIV risk factors.19 Further, in July 2012, the Food and Drug Administration approved the first over-the-counter oral rapid HIV test. These new recommendations and testing technologies may increase screening rates and further decrease the time to presentation.

A recent systematic review found no meaningful increase in CD4 at presentation in developed countries from 1992 to 2011.20 The metaregression used in this analysis only examined CD4 as a continuous linear trend over the study period and did not allow the slope to vary after 2007 as in our analysis and was limited by sparse data over 2010 and 2011. Further, this analysis was unable to adjust for demographic factors. For these reasons, we believe our model better represents the current trends in CD4 at presentation in the United States.

Whites had a higher CD4 at enrollment than did blacks or Hispanics from 2003 to 2011; however, we did observe an increase in CD4 at enrollment for both blacks and Hispanics. Nevertheless, there is a cause for concern in both these racial/ethnic groups. It has long been recognized that blacks carry the largest burden of HIV infection in the United States.17 More recently, a CDC study found that rates of new HIV diagnoses in Hispanics were 2.8-fold higher than in whites in 2010.21 Given that the burden of new HIV diagnoses is in blacks and Hispanics and the slow rate of increase in CD4 count at enrollment, additional targeted efforts focusing on decreasing time to presentation to care are needed in these racial/ethnic groups.

According to our model, MSM had a higher CD4 at enrollment than did subjects with heterosexual risk in all years. This may be due to increased awareness of HIV risk among MSM resulting in increased patient-initiated screening. MSM may also encounter health care more frequently and have increased provider-initiated HIV screening. In contrast to MSM and heterosexual risk, IDU failed to increase mean CD4 at enrollment between 2008 and 2011. In part, this may be driven by low numbers of IDU participants in our study. However, it is also plausible that improvements in screening and linkage to care in MSM and heterosexual risk would not necessarily have a similar impact in IDU.

Consistent with the findings of a prior study that showed subjects ≤35 years old were less likely to present late,11 we found that adult subjects ≤30 years had a higher enrollment CD4 than did those subjects >30 years. Further, we showed that subjects >50 years old did not have any improvement in enrollment CD4 over time, whereas in all other age categories, there was an increase during 2008–2011 (Table 4). It is known that CD4 decreases with age in HIV-seronegative individuals,22 and that older individuals have a lower CD4 after seroconversion.23 To what degree these age-related CD4 effects contribute to the observed disparity is not known. Nevertheless, age-related changes in CD4 should not have affected the annual increase in enrollment CD4 and suggest that there was no decrease in time to presentation to care in patients >50 years between 2008 and 2011. Additional studies to confirm this finding and develop interventions are needed.

This study has several limitations. We sought to determine if time to presentation was decreasing over time and, in particular, after the CDC guideline revision in September 2006; however, it should be noted that there are many other possible explanations for the increasing CD4 at presentation for HIV care after 2008. The changes to the HIV screening guidelines are well documented and occur at the national level, but changes in other aspects of screening such as increased awareness about HIV and improved access to testing may be heterogeneous and represent potential contributing factors that were not directly assessed. HIV-screening practices may have also changed by race/ethnicity over the study period. During 2007–2010, the CDC launched the Expanded Testing Initiative,24 which was focused on increasing HIV testing among blacks and Hispanics. We have no information about participation in the Expanded Testing Initiative by any of our participating sites. Introduction of rapid HIV testing also occurred during the study period, which may have heterogeneously affected local screening practices. This study was not able to directly assess the effect of the many changes in HIV screening that have occurred during the study period.

Similarly, we had no means of assessing time to linkage to care within our cohort, but this can clearly affect time from HIV infection to presentation to care as well. Future studies should assess changes in linkage to HIV care. CD4 is not a perfect surrogate for time to presentation. At the population level, we know that CD4 decline is roughly linear over time,25 but there is a wide individual variation and even variation among race/ethnicity.26–28 However, there is currently no better method for retrospectively assessing time from HIV infection to presentation to care. It is possible that a small portion of our newly presenting subjects had received HIV care before enrollment. We took measures to exclude such patients from analyses; however, we do not have comprehensive access to all outside medical records preceding enrollment. Finally, the HIVRN population is selected from patients who primarily present to urban academic HIV specialty clinics, which limits generalizability.

In summary, we have demonstrated a small, but statistically significant, increase in the CD4 count at enrollment in new presenters to primary HIV care after the revision of the CDC HIV testing guidelines. This increase is encouraging, but many patients continue to present late, and the current rate of increase is slow. Additionally, our study suggests that racial/ethnic, HIV risk factor, and age-related disparities exist in time to presentation to HIV care. Further population-specific efforts are needed to decrease the time from HIV infection to presentation to care.

ACKNOWLEDGMENTS

Participating sites: Alameda County Medical Center, Oakland, CA (Howard Edelstein, MD); Children's Hospital of Philadelphia, Philadelphia, PA (Richard Rutstein, MD); Community Health Network, Rochester, NY (Roberto Corales, DO); Drexel University, Philadelphia, PA (Jeffrey Jacobson, MD, Sara Allen, CRNP); Fenway Health, Boston, MA (Stephen Boswell, MD); Johns Hopkins University, Baltimore, MD (Kelly Gebo, MD, Richard Moore, MD, Allison Agwu, MD); Montefiore Medical Group, Bronx, NY (Robert Beil, MD, Carolyn Chu, MD); Montefiore Medical Center, Bronx, NY (Lawrence Hanau, MD); Oregon Health and Science University, Portland, OR (P. Todd Korthuis, MD); Parkland Health and Hospital System, Dallas, TX (Muhammad Akbar, MD, Laura Armas-Kolostroubis, MD); St Jude's Children's Hospital and University of Tennessee, Memphis, TN (Aditya Gaur, MD); St Luke's Roosevelt Hospital Center, NY, New York (Victoria Sharp, MD, Stephen Arpadi, MD); Tampa General Health Care, Tampa, FL (Charurut Somboonwit, MD); University of California, San Diego, CA (W. Christopher Mathews, MD); Wayne State University, Detroit, MI (Jonathan Cohn, MD). The authors would like to thank Cindy Voss for the management, cleaning, and quality assurance of the data used in this manuscript.

REFERENCES

1. Branson BM, Handsfield HH, Lampe MA, et al.. Revised recommendations for HIV testing of adults, adolescents, and pregnant women in health-care settings. MMWR Recomm Rep. 2006;55(RR-14):1–17; quiz CE11-14.
2. Schwarcz S, Hsu L, Dilley JW, et al.. Late diagnosis of HIV infection: trends, prevalence, and characteristics of persons whose HIV diagnosis occurred within 12 months of developing AIDS. J Acquir Immune Defic Syndr. 2006;43:491–494.
3. Egger M, May M, Chene G, et al.. Prognosis of HIV-1-infected patients starting highly active antiretroviral therapy: a collaborative analysis of prospective studies. Lancet. 2002;360:119–129.
4. Castilla J, Del Romero J, Hernando V, et al.. Effectiveness of highly active antiretroviral therapy in reducing heterosexual transmission of HIV. J Acquir Immune Defic Syndr. 2005;40:96–101.
5. Walensky RP, Weinstein MC, Kimmel AD, et al.. Routine human immunodeficiency virus testing: an economic evaluation of current guidelines. Am J Med. 2005;118:292–300.
6. Paltiel AD, Weinstein MC, Kimmel AD, et al.. Expanded screening for HIV in the United States—an analysis of cost-effectiveness. N Engl J Med. 2005;352:586–595.
7. Sanders GD, Bayoumi AM, Sundaram V, et al.. Cost-effectiveness of screening for HIV in the era of highly active antiretroviral therapy. N Engl J Med. 2005;352:570–585.
8. Gardner EM, McLees MP, Steiner JF, et al.. The spectrum of engagement in HIV care and its relevance to test-and-treat strategies for prevention of HIV infection. Clin Infect Dis. 2011;52:793–800.
9. Centers for Disease Control Prevention. Vital signs: HIV prevention through care and treatment—United States. MMWR Morb Mort Wkly Rep. 2011;60:1618–1623.
10. Althoff KN, Gange SJ, Klein MB, et al.. Late presentation for human immunodeficiency virus care in the United States and Canada. Clin Infect Dis. 2010;50:1512–1520.
11. Buchacz K, Armon C, Palella FJ, et al.. CD4 cell counts at HIV diagnosis among HIV outpatient study participants, 2000–2009. AIDS Res Treatment. 2012;2012:869841.
12. Yehia BR, Gebo KA, Hicks PB, et al.. Structures of care in the clinics of the HIV research network. AIDS Patient Care STDs. 2008;22:1007–1013.
13. Fleishman JA, Gebo KA, Reilly ED, et al.. Hospital and outpatient health services utilization among HIV-infected adults in care 2000–2002. Med Care. 2005;43(9 suppl l):III40–III52.
14. Network HIVR. Hospital and outpatient health services utilization among HIV-infected patients in care in 1999. J Acquir Immune Defic Syndr. 2002;30:21–26.
15. Gebo KA, Fleishman JA, Conviser R, et al.. Racial and gender disparities in receipt of highly active antiretroviral therapy persist in a multistate sample of HIV patients in 2001. J Acquir Immune Defic Syndr. 2005;38:96–103.
16. Gebo KA, Fleishman JA, Reilly ED, et al.. High rates of primary Mycobacterium avium complex and Pneumocystis jiroveci prophylaxis in the United States. Med Care. 2005;43(9 suppl l):III23–III30.
17. Prevention CfDCa. HIV Surveillance Report, 2011. Atlanta, GA: Centers for Disease Control and Prevention; 2013:2013.
18. Prejean J, Song R, Hernandez A, et al.. Estimated HIV incidence in the United States, 2006–2009. PloS One. 2011;6:e17502.
19. Moyer VA. On behalf of the U.S. Preventive Services Task Force. Screening for HIV: U.S. Preventive services task force recommendation statement. Ann Intern Med. 2013;159:51–60.
20. Lesko CR, Cole SR, Zinski A, et al.. A systematic review and meta-regression of temporal trends in adult CD4+ cell count at presentation to HIV care, 1992–2011. Clin Infect Dis. 2013;57:1027–1037.
21. Centers for Disease Control and Prevention. Geographic differences in HIV infection among Hispanics or Latinos—46 states and Puerto Rico, 2010. MMWR Morb Mort Wkly Rep. 2012;61:805–810.
22. Wikby A, Mansson IA, Johansson B, et al.. The immune risk profile is associated with age and gender: findings from three Swedish population studies of individuals 20–100 years of age. Biogerontology. 2008;9:299–308.
23. Potard V, Weiss L, Lamontagne F, et al.. Trends in post-infection CD4 cell counts and plasma HIV-1 RNA levels in HIV-1-infected patients in France between 1997 and 2005. J Acquir Immune Defic Syndr. 2009;52:422–426.
24. Prevention CfDCa. Expanded testing initiative. Available at: http://www.cdc.gov/hiv/policies/eti.html. Accessed June 7, 2013.
25. Williams BG, Dye C. Antiretroviral drugs for tuberculosis control in the era of HIV/AIDS. Science. 2003;301:1535–1537.
26. Muller V, von Wyl V, Yerly S, et al.. African descent is associated with slower CD4 cell count decline in treatment-naive patients of the Swiss HIV Cohort Study. AIDS. 2009;23:1269–1276.
27. May M, Wood R, Myer L, et al.. CD4(+) T cell count decreases by ethnicity among untreated patients with HIV infection in South Africa and Switzerland. J Infect Dis. 2009;200:1729–1735.
28. Pantazis N, Morrison C, Amornkul PN, et al.. Differences in HIV natural history among African and non-African seroconverters in Europe and seroconverters in sub-Saharan Africa. PloS One. 2012;7:e32369.
Keywords:

HIV; CD4 count; presentation to care; linkage to care; HIV screening

© 2014 by Lippincott Williams & Wilkins